---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: google/gemma-7b
model-index:
- name: gemma-7b-prompts
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# gemma-7b-prompts

This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3761

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0004
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7687        | 0.09  | 100  | 1.1701          |
| 0.7207        | 0.19  | 200  | 1.0388          |
| 0.7185        | 0.28  | 300  | 0.9201          |
| 0.9138        | 0.38  | 400  | 0.8356          |
| 0.6879        | 0.47  | 500  | 0.7887          |
| 0.559         | 0.56  | 600  | 0.7439          |
| 0.5832        | 0.66  | 700  | 0.7136          |
| 0.556         | 0.75  | 800  | 0.6738          |
| 0.5783        | 0.85  | 900  | 0.6341          |
| 0.6397        | 0.94  | 1000 | 0.6029          |
| 0.3719        | 1.03  | 1100 | 0.5467          |
| 0.5698        | 1.13  | 1200 | 0.5181          |
| 0.6411        | 1.22  | 1300 | 0.4972          |
| 0.6049        | 1.32  | 1400 | 0.4737          |
| 0.5309        | 1.41  | 1500 | 0.4417          |
| 0.4735        | 1.5   | 1600 | 0.4218          |
| 0.5055        | 1.6   | 1700 | 0.4065          |
| 0.5309        | 1.69  | 1800 | 0.3900          |
| 0.5644        | 1.79  | 1900 | 0.3792          |
| 0.3979        | 1.88  | 2000 | 0.3761          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2